EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, acidity and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). ITS-90 water temperature and Water body salinity variables have been also included (as-is) to complete the Eutrophication and Acidity data. If you use these variables for calculations, please refer to SeaDataNet for having the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets . This aggregated dataset contains all unrestricted EMODnet Chemistry data on Eutrophication and Acidity (14 parameters with quality flag indicators), and covers the North Sea with 587584 CDI records. Data were aggregated and quality controlled by 'Aarhus University, Department of Bioscience, Marine Ecology Roskilde' from Denmark. Regional datasets concerning eutrophication and acidity are automatically harvested and resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all Sea Regions ( https://doi.org/10.6092/9f75ad8a-ca32-4a72-bf69-167119b2cc12). When not present in original data, Water body nitrate plus nitrite was calculated by summing up the Nitrates and Nitrites. Same procedure was applied for Water body dissolved inorganic nitrogen (DIN) which was calculated by summing up the Nitrates, Nitrites and Ammonium. Quality flags for Water body dissolved inorganic nitrogen (DIN) should be disregarded since that currently they are not based on the original quality flags of nitrite, nitrate and ammonium. Parameter names are based on P35, EMODnet Chemistry aggregated parameter names vocabulary, which is available at: https://www.bodc.ac.uk/resources/vocabularies/vocabulary_search/P35/. Detailed documentation is available at: https://dx.doi.org/10.6092/4e85717a-a2c9-454d-ba0d-30b89f742713 Explore and extract data at: https://emodnet-chemistry.webodv.awi.de/eutrophication>NorthSea The aggregated dataset can be downloaded as ODV collection and spreadsheet, which is composed of metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (More information can be found at: http://www.seadatanet.org/Standards-Software/Software/ODV). The original datasets can be searched and downloaded from EMODnet Chemistry Chemistry CDI Data and Discovery Access Service: https://emodnet-chemistry.maris.nl/search

The upper branch of the Atlantic Meridional Overturning Circulation (AMOC) plays a critical role in ocean circulation and climate change, yet its variability during the last glacial period is poorly documented. Here, we investigate the northward-flowing Glacial Eastern Boundary Current (GEBC) in the North Atlantic, known today as the European Slope Current, and representing the easternmost portion of the upper branch of the AMOC. Based on flow speed (sortable silt, XRF) and radiogenic/stable isotopic records, we show that Dansgaard-Oeschger (D/O) interstadials (stadials) correspond to a faster (weaker) GEBC during the ~50-15 ka period. This, by analogy to present-day conditions, suggests enhanced (reduced) strength of the subpolar gyre and, by extension, of northern-sourced water production and AMOC during D-O interstadials (stadials). Concomitant fluctuations of both the European Ice Sheet and the GEBC between ~30 and 17 ka suggest an active role of the upper branch of AMOC in the poleward transport of heat and freshwater to the northern North Atlantic, with direct impacts on deep water formation and AMOC strength. Our GEBC reconstruction is the first physical (non-chemical) record documenting dynamic upper AMOC variability at high resolution in the eastern basin of the North Atlantic. Together with the deep North Atlantic records of northern-sourced water export, they confirm the central role of the AMOC in the generation of abrupt climate changes.

This metadata refers to the EEA marine assessment grid, to which all data and assessment results have been spatially mapped in order to ensure that data can be compared in a uniform way across the European regional seas. The marine assessment grid is based on the EEA reference grid system. The EEA reference grid is based on ERTS89 Lambert Azimuthal Equal Area projection with parameters: latitude of origin 52° N, longitude of origin 10° E, false northing 3 210 000.0 m, false easting 4 321 000.0 m. All grid cells are named with a unique identifier containing information on grid cell size and the distance from origin in meters (easting and northing). An important attribute of the EEA reference grid system is that by using an equal area projection all grid cells are having the same area for the same grid size. In this marine assessment grid, two grid sizes are used: * 100 x 100 km in offshore areas (> 20 km from the coastline) * 20 x 20 km in coastal areas (<= 20 km from the coastline) The grid sizes were choosen after an evaluation of data availability versus the need for sufficient detail in the resulting assessment. The resulting assessment grid is a combination of two grid sizes using the EEA reference grid system. The overall area of interest used in the grid is based on the marine regions and subregions under the Marine Strategy Framework Directive (MSFD). Additionally, Norwegian (Barent Sea and Norwegian Sea) and Icelandic waters (’Iceland Sea’) have been added (see Surrounding seas of Europe). Note that, within the North East Atlantic region, only the subregions within EEZ boundaries (~200 nm) have been included.

The ODIS "Catalogue of Sources" aims to be an online browsable and searchable catalogue of existing ocean related web-based sources/systems of data and information as well as products and services. It will also provide information on products and visualize the landscape (entities and their connections) of ocean data and information sources. It will contribute to the objectives of the Agenda 2030, and in particular the UN Decade for Ocean Science for Sustainable Development. The Catalogue is not an ocean database or metadata repository. The catalogue includes descriptive information such as the URL, title, description, language, point of contact, geographic scope, available technologies for machine-to-machine interaction, keywords, etc. and can be searched on many of these fields. The IODE network of NODCs has been collecting, managing and serving data for decades. This effort has yielded an extensive, but distributed and heterogeneous collection of data and information sources. Additionally, the low threshold for technical capabilities required to offer data and information over the Internet means that many of the hosted resources are not readily discoverable through NODCs, regional or international data and information systems ODIS will provide an online catalogue of (ideally) all online data/information sources (and, where possible, metadata on off-line sources as well). Many regional and international programmes and projects have developed online data/information services but there is currently no "one-stop shop" where users are offered an overview and/or common data/information discovery interface. There are currently 3090 sources (2172 are searchable) catalogued in the system.

Ifremer conducts numerous fisheries surveys dedicated to benthic and demersal populations (commercial / non-commercial fishes and invertebrates). For several years, in application of the ecosystem approach, all benthic invertebrate fauna collected in fishing gear has been systematically monitored: megabenthic invertebrates captured have been sorted, identified, counted and weighted. All these surveys are based on fixed or random stratified sampling strategy with varying intensity depending on the covered survey area. These data are stored, in historical access-based databases or for the most recent years in the centralised “Harmonie” database held in the Ifremer Fishery Information Systeme (SIH). The species nomenclature used was standardized using WoRMS database. Taxa caught at least once a year are listed for each monitoring area on the basis of already available data series. In order to facilitate the identification of individuals sampled on board vessels and to improve the training of onboard scientists, the present work aims to define the minimum level of identification for each of them. The analysis identifies taxa that appears recurrently on available historical series or gathers them on less precise taxonomic levels if this is not the case, which may indicate potential identification difficulties. The following procedure was used: all taxa expressed at the species level were first aggregated at genus level if they occurred less 90% of the years over the available time series. For MEDITS, EPIBENGOL and ORHAGO, the occurrence threshold was set to 70% and to only 50% for NOURMONT because the datasets were less than 10 years long. Then to be kept at that taxonomic level, a given genus had to be observed over 90% of the time (for example over at least 9 years if the dataset contains 10 years). Otherwise it was iteratively regrouped into a higher taxonomic level (family, order, class, division) following the same criteria (Foveau et al, 2017). For instance, for the NOURSEINE survey, this resulted into the aggregation of the 103 origin taxa into 35 taxonomic groups. The name of the final taxon after data processing represents the minimum level of identification defined by the analysis. However, these results are very theoretical. This is why they were sent to scientists who embark regularly in order to refine the level of taxonomic identification with field experience. The first dataset is composed of 8 tables relevant to the different vessel surveys. The first column of each table represents the permanent code of the taxon in the Ifremer taxonomic referential, the second the systematic number and the third the species abbreviated code. The other columns are the different taxonomic levels of the taxon. The minimum level of identification at sea defined by the data processing appears in blue. The level determined by feedback of scientist’s field experience, which is the one to use at sea, appears in green. The second dataset summaries the results detailed in the first table and indicates directly for each taxon identified to far, the minimum level of identification required for the benthic invertebrates by-catch of each fisheries surveys studied.

This visualization product displays the single use plastics (SUP) related items abundance of marine macro-litter (> 2.5cm) per beach per year from non-MSFD monitoring surveys, research & cleaning operations. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols and reference lists used on a European scale. Preliminary processing were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of surveys from non-MSFD monitoring, cleaning and research operations; - Exclusion of beaches without coordinates; - Selection of SUP related items only. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines for Macro Litter on Coastlines from JRC (this document is attached to this metadata); - Exclusion of surveys without associated length; - Normalization of survey lengths to 100m & 1 survey / year: in some case, the survey length was not 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of SUP related items of the survey (normalized by 100 m) = Number of SUP related items of the survey x (100 / survey length) Then, this normalized number of SUP related items is summed to obtain the total normalized number of SUP related items for each survey. Finally, the median abundance of SUP related items for each beach and year is calculated from these normalized abundances of SUP related items per survey. Percentiles 50, 75, 95 & 99 have been calculated taking into account SUP related items from other sources data for all years. More information is available in the attached documents. Warning: the absence of data on the map doesn't necessarily mean that they don't exist, but that no information has been entered in the Marine Litter Database for this area.

This visualization product displays fishing related items density per trawl. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during fishing bottom trawl surveys. In cases where the wingspread and/or the number of items were unknown, data could not be used because these fields are needed to calculate the density. Data collected before 2011 are affected by this filter. When the distance reported in the data was null, it was calculated from: - the ground speed and the haul duration using this formula: Distance (km) = Haul duration (h) * Ground speed (km/h); - the trawl coordinates if the ground speed and the haul duration were not filled in. The swept area is calculated from the wingspread (which depends on the fishing gear type) and the distance trawled: Swept area (km²) = Distance (km) * Wingspread (km) Densities have been calculated on each trawl using the following computation: Density of fishing related items (number of items per km²) = ∑Number of fishing related items / Swept area (km²) Percentiles 50, 75, 95 & 99 have been calculated taking into account data for all years. The list of selected items for this product is attached to this metadata. Information on data processing and calculation is detailed in the attached methodology document. Warning: the absence of data on the map doesn't necessarily mean that they don't exist, but that no information has been entered in the Marine Litter Database for this area.

The Task Force on Hemispheric Transport of Air Pollution (TF HTAP) is an international scientific cooperative effort to improve the understanding of the intercontinental transport of air pollution across the Northern Hemisphere. TF HTAP was organized in 2005 under the auspices of the UNECE Convention on Long-range Transboundary Air Pollution (LRTAP Convention) and reports to the Convention’s EMEP Steering Body. However, participation is open to all interested experts, both inside and outside the UNECE region. TF HTAP organizes scientific cooperation in the areas of emissions inventories and projections, analysis of ambient monitoring and remote sensing, global and regional modeling, and impact assessment to understand the intercontinental flows of ozone and its precursors, fine particles and their components, mercury, and persistent organic pollutants (POPs). The main questions of interest to the TF HTAP relate to the benefits of international cooperation to decrease air pollution emissions: - How do air pollution concentrations (or deposition) in one region of the world change as emissions change in other regions or the world? - How do changes in emissions outside a region affect the health, ecosystem, and climate impacts of air pollution within a given region? - How does the feasibility of further emissions control differ in different regions of the world?

The RAM Legacy Stock Assessment Database is a compilation of stock assessment results for commercially exploited marine populations from around the world. The RAM Legacy Stock Assessment Database is grateful to the many stock assessment scientists whose work this database is based upon and the many collaborators who recorded the assessment model results for inclusion in the RAM Legacy Stock Assessment Database. Since 2011 the RAM Legacy Data base has been hosted and managed at the University of Washington with financial assistance from a consortium of Seattle-based seafood companies and organizations, and from the Walton Family Foundation. Initial development of the database from 2006-2010 was supported by the Census of Marine Life, Canadian Foundation for Innovation, NCEAS, NSERC, the Smith Conservation Research Fellowship, New Jersey Sea Grant, and the National Science Foundation.

The Pélagiques Gascogne (PELGAS, Doray et al., 2000) integrated survey aims at assessing the biomass of small pelagic fish and monitoring and studying the dynamics and diversity of the Bay of Biscay pelagic ecosystem in springtime. PELGAS has been conducted within the EU Common Fisheries Policy Data Collection Framework and Ifremer’s Fisheries Information System. Details on survey protocols and data processing methodologies can be found in Doray et al., (2014, 2017a). This dataset comprises the biomass (in metric tons) and abundance (in thousands of individuals) at length (in cm) of small pelagic fish estimated during the PELGAS survey in the Bay of Biscay in springtime. Total biomass and abundance per species on one hand, and frequencies-at-lenght per species and acoustic Elementary Distance Sampling Units (EDSUs) on the other hand, have been derived from fisheries acoustic and midwater trawl data based on the methodology described in Doray et al. (2010). Frequencies-at-lenght per species and EDSUs have been averaged over the survey area for each species and multiplied by the total biomass and abundance per species, to derive global biomass and abundance at length estimates. This dataset was used in Doray et al., 2017b.